{"id":"W3080415720","doi":"10.1021/acsbiomaterials.0c00713","title":"Comparative Animal Mucomics: Inspiration for Functional Materials from Ubiquitous and Understudied Biopolymers","year":2020,"lang":"en","type":"article","venue":"ACS Biomaterials Science & Engineering","topic":"Silk-based biomaterials and applications","field":"Materials Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Air Force Office of Scientific Research; National Institute on Minority Health and Health Disparities; Division of Integrative Organismal Systems; Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Deutsche Forschungsgemeinschaft; Vicerrectoría de Investigación, Universidad de Costa Rica; Wellcome; Royal Society; City University of New York; Division of Ocean Sciences; Wellcome Trust; Camille and Henry Dreyfus Foundation","keywords":"Mucus; Function (biology); Structure function; Nanotechnology; Biology; Computational biology; Computer science; Evolutionary biology; Ecology; Materials science; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005193499,0.0003236497,0.0004919522,0.0001199809,0.0004917615,0.000700657,0.0003963769,0.0000994314,0.0001513269],"category_scores_gemma":[0.0001124148,0.0002987043,0.00003895644,0.0003742997,0.0004428244,0.0006304374,0.0002149059,0.0000219758,0.00006462656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008620338,"about_ca_system_score_gemma":0.0001028862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001258931,"about_ca_topic_score_gemma":0.000003991204,"domain_scores_codex":[0.9977565,0.00003316846,0.0005591763,0.0008059922,0.0003247558,0.0005203774],"domain_scores_gemma":[0.9990546,0.0001204499,0.0002158675,0.0002357969,0.0001283524,0.0002449625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000140435,0.00002215484,0.00001927471,0.00002536748,0.00001204259,8.917044e-7,0.0005219739,0.0001124077,0.9963408,0.002695538,0.00008648535,0.00002262904],"study_design_scores_gemma":[0.0005893393,0.0001783607,0.002806655,0.0000239312,0.00003303522,0.000003982263,0.0002692644,0.0006370283,0.9947493,0.0000964833,0.0002515791,0.0003610606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915323,0.0001019378,0.004730233,0.0007502782,0.001116507,0.0006523281,0.0007973996,0.000309779,0.000009202069],"genre_scores_gemma":[0.9939994,0.00001062552,0.004691523,0.0003115708,0.0006489721,0.0001932022,0.0001143061,0.00002901918,0.000001350426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00278738,"threshold_uncertainty_score":0.9999465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05099934074692264,"score_gpt":0.2644903837371588,"score_spread":0.2134910429902362,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}